Events
| Event: | Location: | Date: | Time: |
| Compressive Sensing and Applications | Boulder CO | 6/26/2012 | MST 06:00PM-08:30PM |
An Introduction to Compressive Sensing and its Applications
Michael Wakin
When: 6/26/2012 MST 06:00PM-08:30PM
Location: Boulder Beer 2880 Wilderness Place Boulder, CO 80204
Cost: Free
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Abstract:
Over the past several decades, a great deal of attention has been paid in the signal processing and applied mathematics communities to developing effective low-dimensional models for the structure inherent in high-dimensional signals. Indeed, such models are key to addressing the growing challenges of acquiring, storing, and processing ever larger and higher resolution data sets. Recently, an exciting byproduct of this work has been the emergence of a field known as Compressive Sensing (CS). CS is based on the revelation that certain high-dimensional signals obeying low-dimensional models can actually be recovered from small numbers of nonadaptive (even random) linear measurements. In this talk I will provide an introduction to CS, outlining some of its basic theoretical principles and surveying some of its applications in areas such as imaging and sensor networks.
Biography:
Michael B. Wakin received the Ph.D. degree in electrical engineering in 2007 from Rice University. He was an NSF Mathematical Sciences Postdoctoral Research Fellow at the California Institute of Technology from 2006-2007 and an Assistant Professor at the University of Michigan in Ann Arbor from 2007-2008. He is now an Assistant Professor in the Department of Electrical Engineering and Computer Science at the Colorado School of Mines. His research interests include sparse, geometric, and manifold-based models for signal and image processing, approximation, compression, compressive sensing, and dimensionality reduction. In 2007, Dr. Wakin shared the Hershel M. Rich Invention Award from Rice University for the design of a single-pixel camera based on compressive sensing; in 2008, Dr. Wakin received the DARPA Young Faculty Award for his research in compressive multi-signal processing for environments such as sensor and camera networks; and in 2012, Dr. Wakin received the NSF CAREER Award for research into dimensionality reduction techniques for structured data sets.